Q&A – Decomposition & Sub-Routines (Primary 4 – 4CT.06)

Decomposition means breaking a big task into smaller parts.

• True

• False

Answer explanation

True. Decomposition involves breaking a larger task into smaller, manageable parts, making it easier to tackle and complete the overall task.

Which of these is an example of decomposition?

• Writing one long algorithm for everything

• Splitting a program into smaller subroutines like “Input Data,” “Calculate Result,” “Output Result”

• Repeating the same step again and again

• Printing “Hello” 10 times

Answer explanation

Decomposition involves breaking down a complex problem into smaller, manageable parts. The correct choice, "Splitting a program into smaller subroutines like 'Input Data,' 'Calculate Result,' 'Output Result,'" exemplifies this process.

Decomposition is useful in algorithms because:

• it breaks down complex problems into simpler parts.

• it makes algorithms run slower.

• it increases the complexity of problems.

• it hides errors in the code.

Answer explanation

Decomposition is useful in algorithms because it breaks down complex problems into simpler parts, making them easier to understand and solve. This approach enhances problem-solving efficiency.

Which is better, and why?

• Option A is better because it offers more advantages.

• Option B is better because it is more efficient.

• Option C is better because it is more popular.

• Option D is better because it is less expensive.

Answer explanation

Option B is the best choice because efficiency often leads to better performance and productivity, making it a crucial factor in decision-making. While other options have their merits, efficiency is key in many contexts.

Sub-routines can only be used once in an algorithm.

• True

• False

Answer explanation

Sub-routines can be called multiple times within an algorithm, allowing for code reuse and modular design. Therefore, the statement that they can only be used once is false.

Which task benefits most from decomposition?

• Turning on a light switch

• Solving a math problem with 10 steps

• Saying “Hello” once

Answer explanation

Solving a math problem with 10 steps benefits most from decomposition, as breaking it down into smaller, manageable parts makes it easier to understand and solve each step systematically.

How can decomposition help?

• Create a sub-routine called “Paint Line” and repeat it.

• Make the program run faster by default.

• Remove all loops from the code.

• Increase the number of errors in the program.

Answer explanation

Decomposition helps by breaking down complex tasks into smaller, manageable sub-routines, like 'Paint Line'. This allows for easier code maintenance and reuse, enhancing clarity and efficiency in programming.

Q8. Compare Outcomes Two students design a robot dance: • Student A: Writes one long list of 30 steps. • Student B: Breaks it into 3 sub-routines: “Wave Arms,” “Spin,” “Jump.” Who has the better design?

• Student B

• Student A

• Both have equally good designs

• Neither design is good

Answer explanation

Student B's design is better because breaking the dance into sub-routines makes it easier to understand, modify, and debug. This modular approach enhances clarity and organization compared to a single long list.

Q9. Short Answer
Which of the following is a real-life example of decomposition?

• Cooking a meal (sub-routines: wash vegetables, cut ingredients, cook food, serve).

• A glass shattering into pieces

• Water freezing into ice

• A balloon popping

Answer explanation

Cooking a meal involves breaking down the process into smaller tasks (sub-routines) like washing, cutting, cooking, and serving, which exemplifies decomposition. The other options do not involve such systematic breakdown.

Programmers prefer to use decomposition when solving big problems because:

• it breaks down complex problems into smaller, manageable parts.

• it increases the complexity of the problem.

• it makes debugging impossible.

• it reduces the need for planning.

Answer explanation

Programmers use decomposition to simplify complex problems by breaking them into smaller, manageable parts. This approach makes it easier to understand, solve, and debug each component individually.